Ryan Park

Alignment & RLHF · 2024

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Alignment & RLHF — 11 citations into it

Whom Ryan Park trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. John Schulman
2. Leo Gao
3. Nisan Stiennon
4. Paul Christiano
5. Alec Radford
6. Daniel M. Ziegler
7. Rafael Rafailov
8. Jeff Wu
9. Geoffrey E. Hinton
10. Yann Dubois

Papers from Ryan Park's perspective

Ordered by how strongly the researchers Ryan Park trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Language Models are Few-Shot Learners (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Proximal Policy Optimization Algorithms (arXiv.org)
9. Language Models are Unsupervised Multitask Learners
10. ImageNet: A large-scale hierarchical image database

Their papers

• Disentangling Length from Quality in Direct Preference Optimization (2024) — 214 citations